UNIFIED TOPIC-BASED SEMANTIC MODELS: A STUDY IN COMPUTING THE SEMANTIC RELATEDNESS OF GEOGRAPHIC TERMS

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SADR HOSSEIN; Nazari Solimandarabi Mozhdeh; Pedram MirMohsen; Teshnelab Mohammad

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2019 | Issue:5

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Title

UNIFIED TOPIC-BASED SEMANTIC MODELS: A STUDY IN COMPUTING THE SEMANTIC RELATEDNESS OF GEOGRAPHIC TERMS

Author(s)

SADR HOSSEIN | Nazari Solimandarabi Mozhdeh | Pedram MirMohsen | Teshnelab Mohammad

Keywords

SEMANTIC RELATEDNESS

TOPIC-BASED MODELS

LATENT SEMANTIC ANALYSIS

LATENT DIRICHLET ALLOCATION

EXPLICIT SEMANTIC ANALYSIS

GEOGRAPHICAL INFORMATION SCIENCE

Abstract

OVER THE LAST DECADES, A MULTITUDE OF SEMANTIC RELATEDNESS MEASURES HAVE BEEN PROPOSED. DESPITE AN EXTENSIVE AMOUNT OF WORK DEDICATED TO THIS AREA OF RESEARCH, THE UNDERSTANDING OF THEIR FOUNDATION IS STILL LIMITED IN REAL-WORLD APPLICATIONS. IN THIS PAPER, A UNIFYING APPROACH REPRESENTING TOPIC-BASED MODELS IS PROPOSED AND FROM WHICH THE STATE-OF-THEART SEMANTIC RELATEDNESS MEASURES ARE DIVIDED INTO TWO DISTINCT TYPES OF TOPIC-BASED AND ONTOLOGY-BASED MODELS. REGARDLESS OF EXTENSIVE RESEARCHES IN THE FIELD OF ONTOLOGY-BASED MODELS, TOPICBASED MODELS HAVE NOT BEEN TAKEN INTO ACCOUNT CONSIDERABLY. CONSEQUENTLY, THE UNIFIED APPROACH IS ABLE TO HIGHLIGHT EQUIVALENCES AMONG THESE MODELS AND PROPOSE BRIDGES BETWEEN THEIR THEORETICAL BASES. ON THE OTHER HAND, PRESENTING A COMPREHENSIVE UNIFYING APPROACH OF TOPIC-BASED MODELS INDUCES READERS TO HAVE A COMMON UNDERSTANDING OF THEM DESPITE THE DIFFERENCES AND COMPLEXITIES BETWEEN THEIR ARCHITECTURE AND CONFIGURATION DETAILS. IN ORDER TO EVALUATE TOPIC-BASED MODELS IN COMPARISON TO ONTOLOGY-BASED MODELS, COMPREHENSIVE EXPERIMENTS IN THE APPLICATION OF SEMANTIC RELATEDNESS OF GEOGRAPHIC PHRASES HAVE BEEN APPLIED. EMPIRICAL RESULTS HAVE DEMONSTRATED THAT NOT ONLY TOPIC-BASED MODELS IN COMPARISON TO ONTOLOGY-BASED MODELS CONFRONT WITH FEWER RESTRICTIONS IN THE REAL WORLD, BUT ALSO THEIR PERFORMANCE IN COMPUTING SEMANTIC RELATEDNESS OF GEOGRAPHIC PHRASES IS SIGNIFICANTLY SUPERIOR TO ONTOLOGY-BASED MODELS.

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APA: Copy

SADR, HOSSEIN, Nazari Solimandarabi, Mozhdeh, Pedram, MirMohsen, & Teshnelab, Mohammad. (2019). UNIFIED TOPIC-BASED SEMANTIC MODELS: A STUDY IN COMPUTING THE SEMANTIC RELATEDNESS OF GEOGRAPHIC TERMS. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949073/en

Vancouver: Copy

SADR HOSSEIN, Nazari Solimandarabi Mozhdeh, Pedram MirMohsen, Teshnelab Mohammad. UNIFIED TOPIC-BASED SEMANTIC MODELS: A STUDY IN COMPUTING THE SEMANTIC RELATEDNESS OF GEOGRAPHIC TERMS. 2019. Available from: https://sid.ir/paper/949073/en

IEEE: Copy

HOSSEIN SADR, Mozhdeh Nazari Solimandarabi, MirMohsen Pedram, and Mohammad Teshnelab, “UNIFIED TOPIC-BASED SEMANTIC MODELS: A STUDY IN COMPUTING THE SEMANTIC RELATEDNESS OF GEOGRAPHIC TERMS,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2019, [Online]. Available: https://sid.ir/paper/949073/en

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